| Objective:Ovarian cancer is one of the malignant tumors that seriously threaten women’s health.Its incidence rate ranks third among malignant tumors of the female reproductive system.However,because of its tendency to metastasis,drug resistance and recurrence,its 5-year survival rate is only 37%,and its mortality rate ranks first in gynecological malignancies.Studies have shown that alternative splicing(AS)process and ovarian cancer stem cells play important roles in ovarian cancer metastasis,drug resistance and other cancerpromting processes,but the mechanism has not been fully elucidated.Therefore,in this study,the alternative splicing events in ovarian cancer and the role of alternative splicing factor in ovarian cancer stemness maintenance were systematically investigated.Methods:1.Systematic analysis of AS events in ovarian cancer(1)Data download and processing: Download alternative splicing data,RNA sequencing data and corresponding clinical information from the TCGA(https://tcgadata.nci.nih.gov/tcga/)database.(2)Survival analysis: Data of all alternative splicing events from a total of 344 ovarian cancer patients were retrieved for the univariate analysis.Kaplan-Meier survival curves were used to assess prognosis,and alternative splicing events with P<0.05 were considered as candidate prognosis predictors.In addition,the “Survival ROC” R package was used to performReceiver Operating Characteristic Curve(ROC)analysis to assess the sensitivity and specificity of prognostic features.Univariate and multivariate analyses were performed using the "forest map" R package to evaluate the independence of alternative splicing models and clinical characteristics for prognosis prediction.172 patients were randomly selected from the general population(344 samples)to form the validation dataset.(3)Regulation network construction of splicing factors: Splicing factor expression data were retrieved from the TCGA-OC mRNA-seq dataset,and were subjected to one-way COX analysis.(4)Establishment of prognostic models: Use the LASSO(least absolute shrinkage and selection operator)analysis in the "glmnet R" package to screen out the prognostic alternative splicing events in the single factor COX analysis(P<0.05).The prognostic independence of the AS model was then evaluated by multivariate COX analysis.(5)Statistical analysis: All statistical analyses were performed using R 3.5.3(https://www.r-project.org/,v3.5.3)software.P<0.05 was considered statistically significant.2.The role and mechanism of splicing factor hnRNPA1 in promoting stemness maintenance of ovarian cancer cells(1)Analyses of correlations between splicing factor hnRNPA1 and ovarian cancer cell stemness,prognosis and clinicopathological parameters: The expression of the splicing factor was analyzed by gene expression microarray analysis of ovarian cancer cell OVCAR3 vs normal ovarian epithelial cell HOSEpi C(HOSE),ovarian cancer sphere cell OVCAR3 vs HOSE,and OVCAR3 vs OVCAR3 S,and the splicing factors were intersected using Venn diagram.The correlation between hnRNPA1/RBM8 A and stemness markers CD133,CD117,and OCT4 as well as drug resistance marker ABCB1(P-gp)was analyzed using the TCGA platform.Kaplan-Meier Plotter online tools were used to evaluate the correlation between hnRNPA1/RBM8 A and overall survival or progressionfree survival in ovarian cancer patients.The hnRNPA1 protein levels in clinical tissues of ovarian cancer were evaluated by immunohistochemistry.The correlation between hnRNPA1 and clinicopathologic parameters of ovarian cancer patients was analyzed by Pearson chi-square test.The correlation between hnRNPA1 and CD133 and P-gp protein levels in ovarian cancer was analyzed by linear regression.(2)Effects of hnRNPA1 genetic intervention on stemness and drug resistance of ovarian cancer cells: The changes in viability of ovarian cancer cells after overexpression of hnRNPA1 and silence of hnRNPA1 were assessed by CCK-8 cell viability assay and cell colony formation assay.The mRNA and protein levels of CD133 and P-gp were evaluated by q RT-PCR and Western Blot,respectively in cells with hnRNPA1 overexpression or hnRNPA1 silencing.(3)Analyses of correlations between hnRNPA1 and PGK1 or PKM2 splicing protein:GSEA was used to identify hnRNPA1-related pathways;linear regression analysis was used to analyze the correlation between hnRNPA1 and PKM1 or PKM2 in ovarian cancer tissues;q RT-PCR and Western Blot were used to evaluate the expression levels of hnRNPA1 and PKM1/2 in ovarian cells and OVCAR3 cells.The mRNA and protein levels of PKM1 and PKM2 after hnRNPA1 intervention were assessed by q RT-PCR and Western Blot.(4)Analyses of correlations between PKM2 and stemness of ovarian cancer cells and prognosis of ovarian cancer patients: The expression of PKM2 was analyzed based on the Genotype Tissue Expression(GTEx)database with 104 normal ovarian samples and the Cancer Genome Atlas(TCGA)database with 379 ovarian cancer patients.Survival analysis was used to evaluate the correlation between PKM and overall survival(OS)for ovarian cancer patients.Correlation between PKM2 and CD133 and P-gp in TCGA database was evaluated by linear regression.Immunohistochemistry was used to evaluate the expression of PKM1 and PKM2 in clinical ovarian cancer tissue samples and their adjacent normal tissues.The correlation between PKM1 and PKM2 and clinicopathologic parameters of ovarian cancer patients was evaluated by Pearson Chi-square test.Correlation between PKM1/PKM2 and CD133 and P-gp in ovarian cancer tissue samples was evaluated by linear regression.Result:1.Systematic analysis of AS events in ovarian cancer(1)Frequency analysis of alternative splicing events in TCGA-OC: In TCGA-OC data,exon skipping(ES)events are the most common AS type,accounting for more than 1/3 of all AS events,followed by alternative promoter(AP)and alternative terminator(AT)events.Exclusive exons(ME)are the least AS events.The number of AS events far exceeds the number of their corresponding mRNAs.(2)Construction and verification of AS-prognosis evaluation model for AS events: 48,049 variable splicing events were analyzed by univariate COX analysis,and the results showed that 1,429 splicing events co-occurring in 1,125 genes were associated with the prognosis of ovarian cancer.Multiple factor prognostic models were established based on multivariate COX analysis.The combined prognostic model had better predictive performance than single prognostic models.Survival and ROC analyses were carried out in the test dataset containing 172 patients,and indicated that the seven AS models and the combined prognostic model had high prognostic values.Univariate COX analysis showed that the combined prognostic model,tumor status and race were significantly correlated with overall survival of patients;multivariate COX analysis showed that the combined prognostic model and tumor status still had the significant correlation,suggesting that the combined prognostic model and tumor status are independent prognostic factors in patients with ovarian cancer.(3)Advantages of AS-prognostic evaluation models: Kaplan-Meier and ROC analysis show that compared with the mRNA model,the AS model better distinguished the survival of patients and better predicted their prognosis.Therefore,the AS model can be used as a prognostic marker for ovarian cancer patients.(4)AS events and splicing factor regulatory network: 22 splicing factors were significantly associated with 249 prognosis-related AS events.The expression of DDX39 B and MATR3 was inversely correlated with the AT event of PLEKHA7,but positively correlated with the AD event of FLAD1.(5)AS events were associated with stemness: AS events were positively correlated with the expression of CD133 and OCT4.2.Splicing factor hnRNPA1 promotes stemness maintenance in ovarian cancer cells(1)Splicing factor hnRNPA1 was associated with ovarian cancer cell stemness and was correlated with poor prognosis : Gene expression microarray analysis revealed that hnRNPA1 was highly expressed in ovarian cancer cells OVCAR3 and ovarian cancer stem cells OVCAR3 S;Linear regression analysis showed that the expression of hnRNPA1 was positively correlated with the expression of CD133,OCT4,CD117 and P-gp in TCGA ovarian cancer database(n=344);Kaplan Meier Plotter’s online analysis showed that both OS and PFS were lower in ovarian cancer patients with high hnRNPA1 expression than in patients with low hnRNPA1 expression;The protein level of hnRNPA1 was evaluated in104 clinical tissue samples of ovarian cancer.The results showed that compared with benign tissues,ovarian cancer tissues had significantly higher levels of hnRNPA1(P<0.001);Pearson Chi-Square analysis of the correlation between hnRNPA1 expression and clinicopathological parameters showed that hnRNPA1 was highly expressed in patients with III-IV clinical stage,high-level histological grade,lymph node metastasis,and distant metastasis of ovarian cancer(P<0.05);Linear regression analysis showed that hnRNPA1 expression was positively correlated with the expression of CD133 and P-gp.(2)Genetic intervention of hnRNPA1 affects stemness and drug resistance of ovarian cancer cells: Overexpression and silencing of hnRNPA1 were successfully achieved in ovarian cancer parental cells OVCAR3 and sphere cells OVCAR3 S,respectively;CCK-8 cell viability assays showed that overexpression of hnRNPA1 significantly increased the viability of OVCAR3 cells,while silencing hnRNPA1 significantly decreased the viability of OVCAR3 S cells;Colony formation assays showed that the number of colonies in hnRNPA1 overexpressing cells was increased significantly,whereas silence of hnRNPA1 had the opposite effects;The results of q RT-PCR and Western blot showed that the mRNA and protein levels of CD133 and P-gp were significantly increased in the overexpression group of hnRNPA1 in OVCAR3 cells,while the mRNA and protein expressions of CD133 and P-gp were significantly decreased in the silence group of hnRNPA1 in OVCAR3 S cells,suggesting that hnRNPA1 promoted the viability,stemness,and drug resistance of ovarian cancer cells.(3)hnRNPA1 upregulates splicing factor PKM2: Pathway enrichment analysis revealed that hnRNPA1 was mainly enriched in the glycolytic pathway,and hnRNPA1 was associated with PKM exon skipping events.Immunohistochemistry and linear regression analysis showed that hnRNPA1 was positively correlated with PKM2 expression,and inversely correlated with PKM1 expression;q RT-PCR and Western Blot analyses showed that compared with the parental cell line OVCAR3,OVCAR3 S cells had increased mRNA and protein levels of hnRNPA1 and PKM2,but decreased mRNA and protein levels of PKM1;In OVCAR3 cells,compared with the control(NC)group,the hnRNPA1 overexpression group had increased PKM2 expression but decreased PKM1 expression.However,after silencing hnRNPA1 in OVCAR3 S cells,PKM2 expression decreased and PKM1 expression increased.The ratio of PKM2/PKM1 increased after hnRNPA1 overexpression in OVCAR3 cells,but decreased after silencing hnRNPA1 in OVCAR3 S cells.(4)PKM2 is associated with stemness and poor prognosis of ovarian cancer: Analysis of normal ovarian samples retrieved from the GTEx database,and ovarian cancer patient samples retrieved from the TCGA database,as well as corresponding clinical data showed that PKM gene was highly expressed in ovarian cancer tissues compared with normal ovarian tissues,and was significantly associated with poor prognosis in ovarian cancer patients;The expression of PKM was positively correlated with the stemness index(mRNAsi)and the expression of stemness markers CD133 and P-gp;Immunohistochemical analysis of PKM1 and PKM2 showed that protein levels of PKM2 in ovarian cancer tissues were significantly higher than those in benign tissues(P<0.0001),but protein levels of PKM1 in ovarian cancer tissues were significantly lower than those in benign tissues(P<0.0001);Pearson Chi-Square analysis showed that high expression of PKM2 was more frequently found in serous carcinomas,ovarian cancers at III-IV clinical stage or with higher histological grades,lymph node metastasis,or distant metastasis(P<0.05),but high expression of PKM1 was more frequently found in other types of ovarian cancer types(e.g.non-serous carcinomas,ovarian cancers at I-II clinical stage or with lower histological grades,no lymph node metastasis,or no distant metastasis(P<0.05);The expression of PKM2 was positively correlated with the expression of CD133 and Pgp,while the expression of PKM1 is inversely correlated with the expression of CD133 and P-gp.Conclusion:1.We established a prognostic AS model for ovarian cancer patients by systematically analyzing alternative splicing events in ovarian cancers,and found that AS events were associated with stemness.2.Splicing factor hnRNPA1 is highly expressed in ovarian cancers and ovarian cancer stem cells,and is closely related to the poor prognosis of ovarian cancer patients;PKM gene can be mediated by hnRNPA1 through alternative splicing to form two protein subtypes,PKM1 and PKM2,with high expression of PKM2 or low expression of PKM1 closely related to the expression of ovarian cancer stemness markers CD133 and P-gp.3.The shift from PKM1 to PKM2 mediated by hnRNPA1 may be an important mechanism for stemness maintenance of ovarian cancer cells. |
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